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"""Normalization layers for transformers.
Copied from lucidrains:
https://github.com/lucidrains/x-transformers/blob/main/x_transformers/x_transformers.py
"""
import torch
from torch import Tensor, nn
import torch.nn.functional as F
class RMSNorm(nn.Module):
"""Root mean square layer normalization."""
def __init__(self, heads: int, dim: int) -> None:
super().__init__()
self.scale = dim**-0.5
self.gamma = nn.Parameter(torch.ones(heads, 1, dim))
def forward(self, x: Tensor) -> Tensor:
"""Applies normalization."""
return F.normalize(x, dim=-1) * self.scale * self.gamma
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